Breast cancer is a significant health problem in the United States (US) and accounts for more than 40,000 deaths annually. Early detection is cited as one of the best ways to improve long-term prognosis of a patient. The most common method for detection in clinical practice is X-ray mammography, which is generally effective for the broad population of women over 50 years of age. However, screening mammography has substantial limitations, primarily a high false-positive rate (up to 29%), which can result in unnecessary and costly surgical interventions. Breast cancer detection is a particularly challenging problem in younger women and those with radiographically dense breasts. In these cases, the increased levels of fibroglandular tissue can easily obscure small tumors or masquerade as an abnormality because of the tissue overlap on plain film, and as a result, the overall diagnostic performance of mammography can be significantly degraded.
Mammography has other drawbacks from the perspective of the patient, including uncomfortable and painful breast compression and exposure to ionizing radiation. Other clinical standards, such as ultrasound and magnetic resonance imaging (MRI), have also been used to detect breast cancer. As is known by those having ordinary skill in the art, an MR image is typically a high-resolution grey-scale image; however, the MR image lacks in its ability to provide information about the physiological state of the tissue being imaged, of which physical properties such as permittivity and conductivity could be surrogates for that information. While both ultrasound and MRI can achieve high spatial resolution, neither can provide information about the molecular-level changes occurring in breast tissue at the present time.
Microwave imaging spectroscopy (MIS) is based on recovering the electrical properties, namely, permittivity and conductivity, of tissue. Early studies showed a significant dielectric property contrast between normal and malignant breast tissues, however, more recent data indicates that the properties of the normal breast are more variable than originally thought and that the contrast may not be as great for some types of breast tissue. This is particularly true for radiographically denser breasts with higher concentrations of fibroglandular tissue. Notwithstanding, early clinical microwave imaging studies on patients with suspected tumors has demonstrated significant discrimination between those with malignant cancers versus those with benign lesions and other normal tissues. In addition, the non-ionizing and non-compressive nature of microwave imaging makes the technique potentially attractive for cancer screening.
MIS mainly includes solving two problems: a forward problem and an inverse, or optimization, problem. The forward problem involves computing the output from known inputs, namely, microwave excitation, and system properties, such as dielectric property distribution of the tissue being imaged, whereas the inverse problem estimates the properties of an unknown volume, namely dielectric properties of the tissue, from known input, namely, microwave excitation, and measured field values. Since the inverse electromagnetic problem is non-linear, the image reconstruction process is solved iteratively. Moreover, because of its non-linear and ill-posed nature, Gauss-Newton schemes are well suited to the application but require some form of regularization to impose additional constraints.
Regularization is often accomplished by introducing a priori information about the tissue being imaged, which can be necessary to ensure convergence of the reconstruction algorithm to the correct electromagnetic property distribution. In the field of microwave imaging, a number of studies have investigated the incorporation of different types of priors ranging from the internal and/or external shape of the body to information about tissue dielectric properties including their upper and lower bounds.
Given the advantages and limitations of microwave imaging, it would be beneficial to combine the functional information of the microwave imaging with high spatial resolution of other imaging techniques such as, for example, MR.